Coordinated allocation of radio resources to wi-fi and cellular technologies in shared unlicensed frequencies

Wireless connectivity is essential for industrial production processes and workflow management. Moreover, the connectivity requirements of industrial devices, which are usually long-term investments, are diverse and require different radio interfaces. In this regard, the 3GPP has studied how to support heterogeneous radio access technologies (RATs) such as Wi-Fi and unlicensed cellular technologies in 5G core networks. In some cases, these technologies coexist in the same spectrum. Dynamic spectrum sharing (DSS), which has already been proven to increase spectrum efficiency in licensed bands, can also be applied to this scenario. In this paper, we propose two solutions for mobile network operators (MNOs) or service providers to dynamically divide (multiplex) the radio resources of a shared channel between a Wi-Fi basic service set (BSS) and one or several carriers of scheduled wireless networks, such as cellular technologies, with a configurable level of sharing granularity. These solutions do not require modifications to the current commercial off-the-shelf (COTS) end devices. We adapt the existing IEEE 802.11 procedures to notify the Wi-Fi stations that they must share channels with different access networks. We demonstrate that our dynamic sharing proposals are also advantageous over direct coexistence and evaluate each of them quantitatively and qualitatively to determine when one or the other is preferable. The evaluation is particularized for IEEE 802.11ac and long-term evolution (LTE) license assisted access (LAA), but the solutions can be easily extended to 5G new radio-unlicensed (5G NR-U) or to any other wireless technology in which the network side schedules end device transmissions.Agencia Estatal de Investigación | Ref. PID2020-116329GB-C21Xunta de Galicia | Ref. GRC2018/053Fundación La Caix

NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks

With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)